TF_DeleteGraph(g1);
  TF_DeleteGraph(g2);
  TF_DeleteStatus(s);
}
*/

TEST(CAPI, ImportGraphDef) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create a simple graph.
  Placeholder(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_TRUE(TF_GraphOperationByName(graph, "feed") != nullptr);
  TF_Operation* oper = ScalarConst(3, graph, s);

Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.

***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.

### Contributing code

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a

    * C++ API:
        * New virtual methods in the `tflite::SimpleDelegateInterface` class in `tensorflow/lite/delegates/utils/simple_delegate.h`,
          and likewise in the `tflite::SimpleOpaqueDelegateInterface` class in `tensorflow/lite/delegates/utils/simple_opaque_delegate.h`:
            * `CopyFromBufferHandle`
            * `CopyToBufferHandle`
            * `FreeBufferHandle`

}

// Set server_def on the context, possibly updating it.
// TODO(b/291142876) Simplify TFE_ContextSetServerDefWithTimeoutAndRetries and
// TFE_ContextUpdateServerDefWithTimeout to be simple wrappers around the same
// C++ function.
// Retries are used for CreateContext calls, which is used in
// ParameterServerStrategy initialization to be robust to worker preemption.

    packages = [
        "//devtools/python/indexer/...",
        "//learning/brain/keras/...",
        "//learning/brain/mlir/...",
        "//learning/brain/tfrt/...",
        "//learning/lib/ami/simple_ml/...",
        "//learning/pathways/...",
        "//learning/serving/contrib/tfrt/mlir/canonical_ops/...",
        "//learning/serving/experimental/remote_predict/...",

  // Else, only when this is destructed.
  bool persistent_;
};

// Describes a callback for special-cased and more efficient jvp computation.
//
// Could just be a simple typedef in ForwardAccumulator, but MSVC chokes on
// that.
template <typename Gradient>
class ForwardFunction
    : public std::function<Status(const std::vector<Gradient*>&,